Challenging AI Assumptions in Forecasting: Navigating Human Insight and the ML Conundrum

Episode notes

Forecasting in finance has always stirred debate, with a plethora of perspectives on its methodologies and criteria for accuracy. The emergence of AI and machine learning has only added more complexity to an already complex subject. Can these technologies be relied upon to produce dependable and insightful forecasts? And if so, how can finance professionals optimize their utilization to maximize value? In this episode of Fintech Corner JD chats with Yannis Katsaros, Software Engineer at Trovata. Together, they delve into the complexities of uncertainty in forecasting and outline key steps to establish a reliable, balanced approach to leveraging machine learning.

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